After IPO, Straker Shares Rise in First Week of Trading

New Zealand-based Straker Translations pulled off a successful initial public offering on the Australian Stock Exchange in Sydney on October 22, 2018. The company is now listed under the ticker symbol STG. The offer price on the day of the listing was AUD 1.51 and shares jumped 13% on the first day to close at AUD 1.71. The shares traded as high as AUD 1.91 before closing the week at AUD 1.71, giving the company a current market capitalization of AUD 89m (USD 62m).

According to the 150-page listing prospectus, Straker generated revenues of NZD 17.03m (USD 11.02m) in the FY 2018 (ending March 31 2018), incurring a loss on EBITDA-level of NZD 1.8m (USD 1.16m). For the 2019 financial year, Straker projects NZD 23.5m (USD 15.2m) in revenues (buoyed by two recent acquisitions) but still a loss of NZD 2.4m (USD 1.5m) on an EBITDA basis. However, adjusted for the cost of listing (a one-off expense), the company projects a loss of only NZD 0.2m (USD 0.13m) for FY 2019, a significant improvement over the prior year.

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The company sold 26.7% of its shares in the listing, raising AUD 21.2m (USD 14.9m) in the process. Grant Straker, Merryn Straker and Angelina Hunter continue to hold a 13.9% stake in the company post IPO, with investment firm and previous investor Bailador also holding on to a 14.1% stake, according to the prospectus.

Slator 2018 Language Industry M&A and Funding Report

The firm says it plans to invest AUD 13.5m of the IPO proceeds into sales and marketing, product development and customer acquisition as well as potential strategic acquisitions of rival LSPs.

An Interesting Story

To successfully list a mid-sized LSP that’s still generating a loss, Straker needed to tell potential investors an interesting story. In the run up to the IPO and in the prospectus, Straker highlights how “machine learning” is used to streamline its supply chain from order submission and translation production to client delivery on its proprietary translation management platform, called Ray.

Describing its post-editing process, Straker tells investors in the prospectus that “machine learning improves the quality of the initial draft, the amount of review and editing required by human translators declines, increasing the efficiency and productivity of the translation process.”

Furthermore, Straker says its “model differs from many others in the industry in that it charges customers on a rate per word but the translators charge based on an hourly rate”, which “provides significant opportunities (…) to improve margins and offer competitive pricing.”

As a publicly listed language service provider, Straker will now have to report regularly on its progress in translating margin gains into profits on the bottom line.